宁东能源化工基地规划产业布局的生态适宜性分析

基于遥感和地理信息系统技术,在宁东地区土壤侵蚀敏感性评价的基础上,对宁东能源化工基地规划的产业布局进行了生态适宜性分析.结果表明,宁东能源化工基地规划的煤炭、电力和煤化工三大主导产业布 局与该区生态环境不相适宜.在规划的12座煤矿、7个电厂和3个煤化工园区中,有3座煤矿、2个电厂和1个化工园区位于土壤侵蚀的高度敏感区内;有2座煤矿、3个电厂和1个化工园区位于土壤侵蚀的中度敏感区内.为更好的促进区域生态环境与经济社会的协调发展,探索性地提出了宁东能源化工基地产业布局规划的优化调整建议.     

The SITES reserve selection system: A critical review

Numerous models have been put forth to help with the growing demand for the establishment of biodiversity reserves. One site selection model that has been used in several recent studies is SITES [S.J. Andelman, I. Ball, F.W. Davis and D.M. Stoms, SITES V 1.0: an analytical toolbox for designing ecoregional conservation portfolios, Unpublished manual prepared for the nature conservancy, 1999, 1–43. (available at )]. SITES includes two heuristic solvers: based on Greedy and Simulated Annealing. We discuss the formulation of the SITES model, present a new formulation for that problem, and solve a number of test problems optimally using off-the-shelf software. We compared our optimal results with the SITES Simulated Annealing heuristic and found that SITES frequently returns significantly suboptimal solutions. Our results add further support to the argument, started by Underhill [L.G. Underhill, Optimal and suboptimal reserve selection algorithms, Biol. Conserv. 70 (1994) 85–87], continuing through Rodrigues and Gaston [A.S.L. Rodrigues and K.J. Gaston, Optimization in reserve selection procedures – why not?, Biol. Conserv. 107 (2002) 123–129], for greater integration of optimal methods in the reserve design/selection literature.     

Using Insurance to Enhance Nitrogen Fertilizer Application to Reduce Nitrogen Losses to the Environment

The advantage of using insurance to help a farmer adopt a best nitrogen management plan (BNMP) that reduces the impact of agricultural production on the environment is analytically and empirically demonstrated. Using an expected value analysis, it is shown that an insurance program can be structured soas to reduce a farmer's cost of bearing the adoption risk associated with changing production practices and, thus, to improve the farmer's certainty equivalent net return thereby promoting the adoption of a BNMP. Using the adoption of growing-season only N fertilizer application in Iowa as a case study, it is illustrated how insurance may be used to promote the adoption of this practice to reduce N fertilizeruse. It is shown that it is possible for a farmer and an insurance company both to have an incentive to develop an insurance adoption program that will benefit both the farmer and the insurance company, increasing net social welfare and improving environmental quality in Iowa.     

Analyzing the factors affecting environmental risks of projects using a hybrid approach of DEMATEL‐ANP,artificial neural network: A case study

The increasing growth of the economy in each country necessitates a great amount of investment in infrastructure. The belief that projects involve various uncertainties, such as technical skills, management quality, and the like, indicates that most projects fail to achieve their aims, interests, costs, as well as their timeframes and space requirements. As the environment can pose significant uncertainty to any project, environmental risks should be deeply studied by project management departments. This study intends to analyze as a case the environmental risk management system within a consulting firm. From this analysis, each aspect of a project's environmental risk management is ranked using a fuzzy analytical network process (ANP), a neural network algorithm, and a decision‐making trial and evaluation laboratory (DEMATEL) methodology. From the organizational aspect, budget risk is the most significant. From the technical aspect, the risk of regulations is the most important one. Finally, the risk of project failure from poor communication is another identified main risk in this research. By studying high‐ranking items in this hierarchy, it can be understood that these criteria exist in different aspects; therefore, all aspects of the risk should be taken into account to cover and assess risk. A neural network algorithm for validating and reassessment of ranking is employed. Results of this application showed that, based on Spearman's rank correlation method, two different approaches resulted in similar rankings. Finally, some practical implications for responding to the most highly ranked risks are proposed.     

Social consequences associated with the use of various optimization methods in the protection of air quality

The fundamental tactics employed by the EU against air contamination, which are intended to maintain concentrations at a level that does not exceed the permissible values, usually entail considerable expense. To reduce this to a minimum, the procedure of economic optimization of air quality can be applied. When performed for a heavily polluted industrial city, it shows that it is possible to maintain concentrations below the threshold of air quality standards with relatively moderate expenditure. These evaluations also reveal that variations in population density distribution call into question the conventional wisdom that uniform air quality standards provide the best protection against air contamination for a whole region. On the contrary, an optimization that forces a drop in concentration to be evenly spread over the population, without reference to air quality standards, may lead to more efficient protection of human health and make no difference to overall expenditure.     

基于SVM的通风系统故障诊断惩罚系数与核函数系数优化研究

使用支持向量机（SVM）方法对矿井通风系统进行故障诊断,存在惩罚系数（c）和核函数系数（g）,通过人工方法选取效率低、难以达到较高准确率并且出现过拟合的问题。为了提高矿井通风故障诊断的效率、准确率,同时避免过拟合现象,提出了一种改进遗传算法（GA）,在故障诊断过程中对支持向量机的c,g参数进行优化。经过多组试验分析,研究结果表明:用遗传算法优化的SVM矿井通风故障诊断系统相比于未优化系统的故障诊断准确率有所提升,参数未优化前故障诊断的准确率为60%,优化后的准确率为97.894 7%,并且优化参数经过大数据样本验证,未出现过拟合现象,证明了本文提出方法的有效性。     

地铁事故应急疏散模拟及优化研究

为探究如何提高地铁车站应急疏散的效率,以我国近十年来地铁常见事故类型统计为基础,在事故风险分析的前提下,利用风险矩阵和元胞自动机设定应急疏散等级,分析不同事故水平下相应疏散措施。以北京地铁西直门站为实例,使用疏散仿真软件Pathfinder构建模拟环境,对高峰时期下站内最短逃生路径进行疏散模拟;按照事故与疏散的响应过程,从预防次生事故角度出发,针对西直门站疏散过程中可能发生的踩踏事故的诱发因素进行优化;研究拥堵对疏散进度的具体影响,选取使用率较低的M通道设施,进行不同使用率下的多次模拟,得到最优的疏散方案,研究结果可为进一步提高疏散设施利用率、改善应急疏散效果提供技术支持。     

区域应急响应方案柔性生成方法研究

针对目前应急响应方案存在无法适应区域特征的问题,从柔性的角度出发,提出具有区域针对性的应急响应方案生成方法。通过分析区域应急需求,总结方案中的柔性要素;采用层次网络的方式对应急响应方案进行建模,提出要素和要素之间关系的确定方法,并分共性和个性2部分表示应急响应方案柔性生成框架;模拟地震灾害情景,实现柔性应急响应方案生成方法的案例验证,结果表明:该方法可以反映区域特点,高效有序并有针对性地完成有关突发事件的应对工作。     

基于改进PSO-BPNN的输油管道内腐蚀速率研究

为解决输油管道易腐蚀,且腐蚀程度难以测量的问题,提出使用改进的粒子群算法（PSO）优化误差反向传播神经网络（BPNN）对输油管道内腐蚀速率进行预测。改进的PSO算法提升了自身搜索到全局最优的能力,可为BPNN提供最优初始权值和阈值,从而有效避免BPNN易陷入局部最优的问题发生。以某条输油管线为例,分别运用标准的BPNN模型、PSO-BPNN以及改进的PSO-BPNN对该管线内腐蚀速率进行预测。结果表明:基于改进的PSO-BPNN的预测结果平均相对误差为5.57%,预测精度较BPNN和PSO-BPNN有明显提升。使用改进的PSO-BPNN预测输油管道的腐蚀速率可为管道的检测维修提供可靠的理论和技术支撑。